Triple
T30299931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NSArray |
E770627
|
entity |
| Predicate | storesRetainedObjects |
P6164
|
FINISHED |
| Object | YES |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: YES | Statement: [NSArray, storesRetainedObjects, YES]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storesRetainedObjects Context triple: [NSArray, storesRetainedObjects, YES]
-
A.
storesObjectsAs
Indicates that one entity keeps or maintains other entities within it as stored items or contents.
-
B.
proposedToRetain
Indicates that one entity has suggested or decided to keep or continue maintaining another entity in its current role, state, or possession.
-
C.
leavesObjectsIn
Indicates that an agent or entity causes objects to remain or be left within a particular location or container.
-
D.
retained
chosen
Indicates that one entity keeps possession, control, or continued engagement of another entity over a period of time.
-
E.
favoriteObjectsToCount
Indicates that an entity has particular objects it prefers or most commonly chooses when performing counting activities.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f224881b948190b8c4921b250a44a3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6813976048190be49bb86744b2fb2 |
completed | May 2, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:48 p.m.